With the advance in technologies, color images or videos can be captured conveniently through various devices like digital cameras, cell phone cameras, and video recorders. Color itself can provide people with much more information than monochrome, and people are so used to color images that they prefer to view and print images in color with color displays and color printers, which are abundantly available.
The importance of color imaging has made its quality become essential to users. However, color noise is largely unavoidable owing to color interpolation on Mosaic sensors and electronic noise from circuits and cables, for instance. Color noise exists independently in each color, and people endeavor to reduce any existing color noise in images.
Low-pass filtering is a conventional way to reduce color noise, because noise normally comprises irregularities in an image and typically is regarded as such high-frequency components of an image. Consequently, low-pass filter can reduce such noise. However, since edges or color edges represent sharp changes and are made substantially of high-frequency components, edges are blurred if low-pass filtering is applied.
In an attempt to overcome the deficiencies of the low-pass filtering, techniques have been proposed that identify edges in an image to avoid blurring of such desired color transitions. For example, U.S. Pat. No. 5,241,370 issued on Aug. 31, 1993 to Desor describes using correlation to identify color transitions. The color transition is enhanced before the low-pass filtering is applied to maintain the sharpness. However, the technique only works on television signals and emphasizes on the horizontal transition only. Furthermore, a vertical digital filter must be used in this method.
U.S. Pat. No. 5,432,869 issued to Matsumoto on Jul. 11, 1995 describes the same principles. The problem of direction-oriented filtering has again made it less effective. Another way to retain the sharpness while suppressing the noise is discriminating the noise components from the edges as in U.S. Pat. No. 6,667,815 B1 issued to Nagao on Dec. 23, 2003 where edge detection is used to characterize the edges and then suppress only the noise that is separated according to color correlation. The method also enhances the image sharpness.
U.S. Patent Application Publication No. 20060050182A1 published on Mar. 9, 2006 in the name of Lee describes an adaptive color correction method in which chrominance of a pixel is adjusted according to the corresponding luminance of the pixel by a weighting procedure, resulting in an undesirable performance that the color-noise reduction is luminance-biased. Furthermore, no sharpening measures are adopted, making the blurring of edges unavoidable.
U.S. Patent Application Publication No. 20060055985A1 published on Mar. 16, 2006 in the name of Ikeda and U.S. Pat. No. 6,980,326 B2 issued to Tsuchiya on Dec. 27, 2005 describe noise suppression without sharpness degradation. Both use edge detection because the prior knowledge of edges in filter design is required to preserve the edges.
The foregoing problems of preserving the color for small objects and of edge detection and image sharpening are costly in computation.
Apart from color preserving on small objects and computational complexity issues, the above conventional technologies may lead to undesirable performance. Firstly, such conventional methods rely on luminance components and hence the resulting performance is luminance-biased. Secondly, adopting the use of fixed thresholding, luminance-biased and single-directional edge detection limits the suppression capability, which results in limited performance.
Thus, a need clearly exists for an improved method for color denoising.